Let’s define some vectors which can be used for demonstrations:
manyNumbers <- sample( 1:1000, 20 )
manyNumbers
[1] 692 76 751 633 474 625 532 756 840 528 80 277 496 534 860 502 842 507 196 531
manyNumbersWithNA <- sample( c( NA, NA, NA, manyNumbers ) )
manyNumbersWithNA
[1] 840 80 NA 756 277 502 507 76 534 860 842 196 625 751 532 NA 528 633 531 496 692 474 NA
duplicatedNumbers <- sample( 1:5, 10, replace = TRUE )
duplicatedNumbers
[1] 1 3 3 4 2 4 3 4 4 3
letters
[1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s" "t" "u" "v" "w" "x" "y" "z"
LETTERS
[1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R" "S" "T" "U" "V" "W" "X" "Y" "Z"
mixedLetters <- c( sample( letters, 5 ), sample( LETTERS, 5 ) )
mixedLetters
[1] "k" "e" "n" "a" "s" "Y" "T" "J" "Z" "H"
manyNumbersWithNA instead of manyNumbers.all( manyNumbers <= 1000 )
[1] TRUE
all( manyNumbers <= 500 )
[1] FALSE
any( manyNumbers > 1000 )
[1] FALSE
any( manyNumbers > 500 )
[1] TRUE
all( !is.na( manyNumbers ) )
[1] TRUE
any( is.na( manyNumbers ) )
[1] FALSE
Input: logical vector Output: vector of numbers (positions)
which( manyNumbers > 900 )
integer(0)
which( manyNumbersWithNA > 900 )
integer(0)
which( is.na( manyNumbersWithNA ) )
[1] 3 16 23
manyNumbers[ manyNumbers > 900 ] # indexing by logical vector
integer(0)
manyNumbers[ which( manyNumbers > 900 ) ] # indexing by positions
integer(0)
somePositions <- which( manyNumbers > 900 )
manyNumbers[ somePositions ]
integer(0)
"A" %in% LETTERS
[1] TRUE
c( "X", "Y", "Z" ) %in% LETTERS
[1] TRUE TRUE TRUE
all( c( "X", "Y", "Z" ) %in% LETTERS )
[1] TRUE
all( mixedLetters %in% LETTERS )
[1] FALSE
any( mixedLetters %in% LETTERS )
[1] TRUE
mixedLetters[ mixedLetters %in% LETTERS ]
[1] "Y" "T" "J" "Z" "H"
mixedLetters[ !( mixedLetters %in% LETTERS ) ]
[1] "k" "e" "n" "a" "s"
manyNumbers %in% 300:600
[1] FALSE FALSE FALSE FALSE TRUE FALSE TRUE FALSE FALSE TRUE FALSE FALSE TRUE TRUE FALSE TRUE FALSE TRUE
[19] FALSE TRUE
which( manyNumbers %in% 300:600 )
[1] 5 7 10 13 14 16 18 20
sum( manyNumbers %in% 300:600 )
[1] 8
NAsif_else( manyNumbersWithNA >= 500, "large", "small" )
[1] "large" "small" NA "large" "small" "large" "large" "small" "large" "large" "large" "small" "large" "large"
[15] "large" NA "large" "large" "large" "small" "large" "small" NA
if_else( manyNumbersWithNA >= 500, "large", "small", "UNKNOWN" )
[1] "large" "small" "UNKNOWN" "large" "small" "large" "large" "small" "large" "large" "large"
[12] "small" "large" "large" "large" "UNKNOWN" "large" "large" "large" "small" "large" "small"
[23] "UNKNOWN"
# here integer 0L is needed instead of real 0.0
# manyNumbersWithNA contains integer numbers and the method complains
if_else( manyNumbersWithNA >= 500, manyNumbersWithNA, 0L )
[1] 840 0 NA 756 0 502 507 0 534 860 842 0 625 751 532 NA 528 633 531 0 692 0 NA
unique( duplicatedNumbers )
[1] 1 3 4 2
unique( c( NA, duplicatedNumbers, NA ) )
[1] NA 1 3 4 2
duplicated( duplicatedNumbers )
[1] FALSE FALSE TRUE FALSE FALSE TRUE TRUE TRUE TRUE TRUE
which.max( manyNumbersWithNA )
[1] 10
manyNumbersWithNA[ which.max( manyNumbersWithNA ) ]
[1] 860
which.min( manyNumbersWithNA )
[1] 8
manyNumbersWithNA[ which.min( manyNumbersWithNA ) ]
[1] 76
range( manyNumbersWithNA, na.rm = TRUE )
[1] 76 860
manyNumbersWithNA
[1] 840 80 NA 756 277 502 507 76 534 860 842 196 625 751 532 NA 528 633 531 496 692 474 NA
sort( manyNumbersWithNA )
[1] 76 80 196 277 474 496 502 507 528 531 532 534 625 633 692 751 756 840 842 860
sort( manyNumbersWithNA, na.last = TRUE )
[1] 76 80 196 277 474 496 502 507 528 531 532 534 625 633 692 751 756 840 842 860 NA NA NA
sort( manyNumbersWithNA, na.last = TRUE, decreasing = TRUE )
[1] 860 842 840 756 751 692 633 625 534 532 531 528 507 502 496 474 277 196 80 76 NA NA NA
manyNumbersWithNA[1:5]
[1] 840 80 NA 756 277
order( manyNumbersWithNA[1:5] )
[1] 2 5 4 1 3
rank( manyNumbersWithNA[1:5] )
[1] 4 1 5 3 2
sort( mixedLetters )
[1] "a" "e" "H" "J" "k" "n" "s" "T" "Y" "Z"
manyDuplicates <- sample( 10:15, 10, replace = TRUE )
rank( manyDuplicates )
[1] 8.5 8.5 2.5 6.0 5.0 2.5 2.5 2.5 8.5 8.5
rank( manyDuplicates, ties.method = "min" )
[1] 7 7 1 6 5 1 1 1 7 7
rank( manyDuplicates, ties.method = "random" )
[1] 8 9 4 6 5 3 1 2 10 7
v <- c( -1, -0.5, 0, 0.5, 1, rnorm( 10 ) )
v
[1] -1.0000000 -0.5000000 0.0000000 0.5000000 1.0000000 -1.7573167 0.4183369 0.1402900 1.4431644 -1.7079912
[11] 1.2588231 0.2619085 0.2643704 1.9361729 0.3206620
round( v, 0 )
[1] -1 0 0 0 1 -2 0 0 1 -2 1 0 0 2 0
round( v, 1 )
[1] -1.0 -0.5 0.0 0.5 1.0 -1.8 0.4 0.1 1.4 -1.7 1.3 0.3 0.3 1.9 0.3
round( v, 2 )
[1] -1.00 -0.50 0.00 0.50 1.00 -1.76 0.42 0.14 1.44 -1.71 1.26 0.26 0.26 1.94 0.32
floor( v )
[1] -1 -1 0 0 1 -2 0 0 1 -2 1 0 0 1 0
ceiling( v )
[1] -1 0 0 1 1 -1 1 1 2 -1 2 1 1 2 1
heights <- c( Amy = 166, Eve = 170, Bob = 177 )
heights
Amy Eve Bob
166 170 177
names( heights )
[1] "Amy" "Eve" "Bob"
names( heights ) <- c( "AMY", "EVE", "BOB" )
heights
AMY EVE BOB
166 170 177
heights[[ "EVE" ]]
[1] 170
expand_grid( x = c( 1:3, NA ), y = c( "a", "b" ) )
# A tibble: 8 × 2
x y
<int> <chr>
1 1 a
2 1 b
3 2 a
4 2 b
5 3 a
6 3 b
7 NA a
8 NA b
combn( c( "a", "b", "c", "d", "e" ), m = 2, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "b" "b" "b" "c" "c" "d"
[2,] "b" "c" "d" "e" "c" "d" "e" "d" "e" "e"
combn( c( "a", "b", "c", "d", "e" ), m = 3, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "a" "a" "b" "b" "b" "c"
[2,] "b" "b" "b" "c" "c" "d" "c" "c" "d" "d"
[3,] "c" "d" "e" "d" "e" "e" "d" "e" "e" "e"
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